Instructions to use HomeBrewedLabs/metallum-1b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use HomeBrewedLabs/metallum-1b with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="HomeBrewedLabs/metallum-1b", trust_remote_code=True)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("HomeBrewedLabs/metallum-1b", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use HomeBrewedLabs/metallum-1b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "HomeBrewedLabs/metallum-1b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "HomeBrewedLabs/metallum-1b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/HomeBrewedLabs/metallum-1b

SGLang

How to use HomeBrewedLabs/metallum-1b with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "HomeBrewedLabs/metallum-1b" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "HomeBrewedLabs/metallum-1b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "HomeBrewedLabs/metallum-1b" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "HomeBrewedLabs/metallum-1b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use HomeBrewedLabs/metallum-1b with Docker Model Runner:
```
docker model run hf.co/HomeBrewedLabs/metallum-1b
```

metallum-1b / NOTICE

HomeBrewedLabs

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	Metallum-1B
	Copyright 2026 Home Brewed Labs

	This product includes model weights trained in part on the `stack_ml_edu`
	portion of the pretraining corpus (2.973B pack tokens, 15.3% of the pack),
	which is derived from Stack Exchange content.

	Stack Exchange content is licensed under CC BY-SA 4.0
	(https://creativecommons.org/licenses/by-sa/4.0/). Attribution is owed to
	the Stack Exchange contributors (https://stackexchange.com/). The
	share-alike obligation attaches to that portion of the training data.

	The model weights and code in this repository are licensed under
	Apache-2.0 (see LICENSE). This NOTICE does not modify the License.